论文标题
内源性二元治疗的无条件政策影响的识别和估计：无条件的MTE方法
Identification and Estimation of Unconditional Policy Effects of an Endogenous Binary Treatment: An Unconditional MTE Approach
论文作者
论文摘要
本文研究了治疗状态是二元和内源性时的识别和估计。我们根据策略目标的功能功能的影响功能引入了新的边际治疗效果（MTE）。我们表明，无条件的政策效应可以表示为对待遇状况无动于衷的个人的新定义MTE的加权平均值。我们为无条件政策效应的点识别提供了条件。当分位数是感兴趣的功能时，我们引入了无条件的仪器分位数估计器（唯一）并建立其一致性和渐近分布。在经验应用中，我们估计了由较高的学费补贴引起的大学入学率变化对工资分布的分位数的影响。
This paper studies the identification and estimation of policy effects when treatment status is binary and endogenous. We introduce a new class of marginal treatment effects (MTEs) based on the influence function of the functional underlying the policy target. We show that an unconditional policy effect can be represented as a weighted average of the newly defined MTEs over the individuals who are indifferent about their treatment status. We provide conditions for point identification of the unconditional policy effects. When a quantile is the functional of interest, we introduce the UNconditional Instrumental Quantile Estimator (UNIQUE) and establish its consistency and asymptotic distribution. In the empirical application, we estimate the effect of changing college enrollment status, induced by higher tuition subsidy, on the quantiles of the wage distribution.
